U.S. patent application number 17/298727 was filed with the patent office on 2022-02-17 for robot cleaner and method for operating same.
The applicant listed for this patent is LG ELECTRONICS INC.. Invention is credited to Junghwan KIM, Minho LEE.
Application Number | 20220047135 17/298727 |
Document ID | / |
Family ID | 1000005987945 |
Filed Date | 2022-02-17 |
United States Patent
Application |
20220047135 |
Kind Code |
A1 |
LEE; Minho ; et al. |
February 17, 2022 |
ROBOT CLEANER AND METHOD FOR OPERATING SAME
Abstract
A robot cleaner according to an embodiment of the present
invention comprises: a travelling part for moving a body; a memory
for storing travel state information of the traveling part, which
is recorded while a cleaning operation is performed on the basis of
a first map; and a control part for discriminately detecting a
first area and a second area divided from a plurality of cleaning
areas corresponding to the first map, on the basis of the stored
travel state information. Moreover, the control part may generate a
second map by removing one of the first area and the second area
from the first map, and then control the travelling part to perform
a cleaning operation in a changed cleaning mode on the basis of the
generated second map.
Inventors: |
LEE; Minho; (Seoul, KR)
; KIM; Junghwan; (Seoul, KR) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
LG ELECTRONICS INC. |
Seoul |
|
KR |
|
|
Family ID: |
1000005987945 |
Appl. No.: |
17/298727 |
Filed: |
December 10, 2019 |
PCT Filed: |
December 10, 2019 |
PCT NO: |
PCT/KR2019/017350 |
371 Date: |
June 1, 2021 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A47L 9/2805 20130101;
G05D 2201/0215 20130101; A47L 9/2842 20130101; A47L 2201/04
20130101; G05D 1/0219 20130101; G05D 2201/0203 20130101; G05D
1/0274 20130101; A47L 2201/06 20130101; A47L 9/2852 20130101; A47L
11/4011 20130101; A47L 11/4066 20130101 |
International
Class: |
A47L 9/28 20060101
A47L009/28; A47L 11/40 20060101 A47L011/40; G05D 1/02 20060101
G05D001/02 |
Foreign Application Data
Date |
Code |
Application Number |
Dec 12, 2018 |
KR |
10-2018-0160300 |
Dec 12, 2018 |
KR |
10-2018-0160301 |
Claims
1. A robot cleaner, comprising: a driving unit that moves a main
body; a memory that stores driving state information of the driving
unit recorded while performing a cleaning operation based on a
first map; and a controller that finds a plurality of cleaning
areas corresponding to the first map by dividing them into a first
area and a second area based on the stored driving state
information, wherein the controller generates a second map by
removing either one of the first area and the second area from the
first map, and performs a cleaning operation in a varied cleaning
mode based on the generated second map.
2. The robot cleaner of claim 1, wherein the controller sets a
virtual boundary in an area removed from the first map using the
second map, and controls the driving unit to perform a cleaning
operation by avoiding the set virtual boundary.
3. The robot cleaner of claim 1, wherein the controller controls
the driving unit to perform a cleaning operation in a first
cleaning mode for a cleaning area included in the second map, and
perform a cleaning operation in a second cleaning mode different
from the first cleaning mode for a cleaning area of the first map
that is not included in the second map.
4. The robot cleaner of claim 3, wherein the second map comprises
cleaning areas in which cleaning obstruction areas have been
removed from the first map based on the stored driving state
information, and the first cleaning mode is a quick cleaning mode,
and the second cleaning mode is determined differently according to
driving state information recorded in each of the cleaning
obstruction areas.
5. The robot cleaner of claim 4, wherein the driving state
information recorded in each of the cleaning obstruction areas
comprises at least one of a driving path, a driving speed of the
main body recorded in each of the cleaning obstruction areas, a
number of wheel rotations of the main body, a number of changes in
the driving direction of the main body, and a time taken to exit
the relevant cleaning area.
6. The robot cleaner of claim 1, wherein the controller sets at
least part of the cleaning area of the first map that is not
included in the second map as a cleaning attention area and adds it
to the second map based on the stored driving state
information.
7. The robot cleaner of claim 6, wherein the controller increases
the sensitivity level of at least one sensor provided in the main
body than before while performing a cleaning operation in the
cleaning attention area using the second map.
8. The robot cleaner of claim 7, wherein the controller recovers or
decreases the sensitivity level of the sensor in response to
sensing that the main body is out of the cleaning attention
area.
9. The robot cleaner of claim 6, wherein the controller outputs a
control command for increasing a rotation speed of a suction motor
provided in the main body than before while performing a cleaning
operation for the cleaning attention area using the second map.
10. The robot cleaner of claim 6, wherein the controller decreases
a driving speed of the main body by the driving unit than before
while performing a cleaning operation in the cleaning attention
area using the second map.
11. The robot cleaner of claim 1, wherein the generated second map
and data related to the second map are stored in the memory, and
the controller calls the stored second map and the data related to
the second map from the memory in response to receiving a driving
signal for the cleaning operation.
12. A method of operating a robot cleaner, the method comprising:
storing driving state information of a main body recorded while
performing a cleaning operation based on a first map; finding a
plurality of cleaning areas corresponding to the first map by
dividing them into a first area and a second area based on the
stored driving state; generating a second map by removing either
one of the first area and the second area from the first map; and
performing a cleaning operation in a varied cleaning mode based on
the generated second map.
13. The method of claim 12, wherein said generating a second map
comprises: removing a cleaning obstruction area from the first map
based on the stored driving state information; and setting at least
part of the cleaning area of the first map that is not included in
the second map as a cleaning attention area and adding it to the
second map based on the stored driving state information.
14. The method of claim 13, wherein said performing a cleaning
operation in a varied cleaning mode comprises: setting cleaning
areas other than the cleaning attention area in the second map to a
first cleaning mode, and setting the cleaning attention area to a
second cleaning mode different from the first cleaning mode; and
excluding an area of the first map that is not included in the
second map from the cleaning area.
15. The method of claim 14, wherein the first cleaning mode is a
quick cleaning mode, and the second cleaning mode is a cleaning
mode in which at least one of a driving speed of the main body, a
sensitivity level of a sensor provided in the main body, and a
rotation speed of a suction motor provided in the main body is
changed based on driving state information recorded in each
cleaning obstruction area.
Description
BACKGROUND
1. Technical Field
[0001] The present disclosure relates to a robot cleaner capable of
performing cleaning while driving autonomously, and more
specifically, to a robot cleaner capable of performing cleaning
while driving autonomously in a cleaning area based on a map, and
an operating method thereof.
2. Description of the Related Art
[0002] A cleaner is a device that performs cleaning by sucking or
mopping dust or foreign materials. In general, the cleaner performs
a cleaning function for a floor, and includes wheels for movement.
In general, the wheels are rolled by external force applied to the
cleaner main body to move the cleaner main body relative to the
floor.
[0003] However, in recent years, researches on an autonomous
cleaner such as a robot cleaner that performs cleaning while
driving on its own without a user's manipulation, and a cleaner
that moves on its own along a nozzle moved by a user's manipulation
have been actively carried out.
[0004] With the development of such a robot cleaner performing
cleaning while driving by itself without a user's operation, there
is a need to develop a plurality of robot cleaners for performing
cleaning while any one thereof follows another one thereof or while
collaborating with each other without a user's operation.
[0005] This robot cleaner initially performs cleaning while
searching and moving all unknown areas. Then, afterwards, learning
cleaning is performed based on a map generated based on the
search.
[0006] However, even in the case of learning cleaning, it is
designed to clean all areas by considering the coverage of the
entire cleaning area as important. Accordingly, in a complex
environment such as a plurality of obstacles or an uneven floor
condition, cleaning completion time is lengthened, which may be
frustrating for the user.
[0007] Accordingly, Korean Patent Application Publication No.
KR101807484 discloses a method of performing a cleaning operation
with a map generated based on sensor information acquired through a
sensor provided in a robot cleaner.
[0008] However, the method has a disadvantage that it is difficult
to apply to a robot cleaner with insufficient sensors, and the
accuracy is poor due to various environmental variables.
SUMMARY
[0009] Accordingly, an aspect of the present disclosure is to
provide a robot cleaner capable of generating a map that is robust
to various environmental variables and highly usable without
relying on sensors, and an operation method thereof.
[0010] Furthermore, another aspect of the present disclosure is to
provide a robot cleaner capable of finding cleaning obstruction
areas in which the driving of the main body is complicated from an
existing map and reflecting them on a new map without relying on
sensors, and an operation method thereof.
[0011] In addition, still another aspect of the present disclosure
is to provide a robot cleaner capable of finding cleaning
obstruction areas in which the driving of the main body is
complicated from an existing map, and discovering and setting a new
cleaning mode based on the found cleaning obstruction areas, and an
operation method thereof.
[0012] Moreover, yet still another aspect of the present disclosure
is to provide a robot cleaner capable of cleaning the found
cleaning obstruction areas and the remaining cleaning area in
different cleaning modes, and cleaning each of the detected
cleaning obstruction areas in different cleaning modes suitable for
the environment, and an operation method thereof.
[0013] A robot cleaner according to an embodiment of the present
disclosure may include a driving unit that moves a main body; a
memory that stores driving state information of the driving unit
recorded while performing a cleaning operation based on a first
map; and a controller that finds a plurality of cleaning areas
corresponding to the first map by dividing them into a first area
and a second area based on the stored driving state information,
wherein the controller generates a second map by removing either
one of the first area and the second area from the first map, and
performs a cleaning operation in a varied cleaning mode based on
the generated second map.
[0014] Furthermore, in an embodiment, the controller may set a
virtual boundary in an area removed from the first map using the
second map, and control the driving unit to perform a cleaning
operation by avoiding the set virtual boundary.
[0015] Furthermore, in an embodiment, the controller may control
the driving unit to perform a cleaning operation in a first
cleaning mode for a cleaning area included in the second map, and
perform a cleaning operation in a second cleaning mode different
from the first cleaning mode for a cleaning area of the first map
that is not included in the second map.
[0016] Furthermore, in an embodiment, the second map may include
cleaning areas in which cleaning obstruction areas have been
removed from the first map based on the stored driving state
information, and the first cleaning mode may be a quick cleaning
mode, and the second cleaning mode may be determined differently
according to driving state information recorded in each of the
cleaning obstruction areas.
[0017] Furthermore, in an embodiment, the driving state information
recorded in each of the cleaning obstruction areas may include at
least one of a driving path, a driving speed of the main body
recorded in each of the cleaning obstruction areas, a number of
wheel rotations of the main body, a number of changes in the
driving direction of the main body, and a time taken to exit the
relevant cleaning area.
[0018] Furthermore, in an embodiment, the controller may set at
least part of the cleaning area of the first map that is not
included in the second map as a cleaning attention area and add it
to the second map based on the stored driving state
information.
[0019] Furthermore, in an embodiment, the controller may increase
the sensitivity level of at least one sensor provided in the main
body than before while performing a cleaning operation in the
cleaning attention area using the second map.
[0020] Furthermore, in an embodiment, the controller may recover or
decrease the sensitivity level of the sensor in response to sensing
that the main body is out of the cleaning attention area.
[0021] Furthermore, in an embodiment, the controller may output a
control command for increasing a rotation speed of a suction motor
provided in the main body than before while performing a cleaning
operation for the cleaning attention area using the second map.
[0022] Furthermore, in an embodiment, the controller may decrease a
driving speed of the main body by the driving unit than before
while performing a cleaning operation in the cleaning attention
area using the second map.
[0023] Furthermore, in an embodiment, the generated second map and
data related to the second map may be stored in the memory, and the
controller may call the stored second map and the data related to
the second map from the memory in response to receiving a driving
signal for the cleaning operation.
[0024] Furthermore, a robot cleaner according to another embodiment
of the present disclosure may include a driving unit that moves a
main body; and a controller that collects driving state information
by the driving unit while cleaning is performed based on a first
map, wherein the controller finds cleaning obstruction areas in
which the driving of the driving unit is complicated from the first
map, and generates a second map corresponding to the first map
based on the found cleaning obstruction areas.
[0025] Furthermore, in an embodiment, the driving state information
may be collected in a cell unit for each of a plurality of cells
constituting the first map.
[0026] Furthermore, in an embodiment, the driving state information
may include information on a motion of the driving unit
corresponding to a situation sensed through at least one sensor
provided in the main body.
[0027] Furthermore, in an embodiment, the sensed situation may
include at least one of sensing of an obstacle existing in a
driving path, sensing of a ground state of the driving path,
sensing of a wheel falling off of the main body, sensing of a
collision of the main body, sensing of a wheel slip of the main
body, sensing of wall following, sensing of a virtual wall, sensing
of a cliff, and sensing of a learned trap area.
[0028] Furthermore, in an embodiment, a motion of the driving unit
corresponding to the sensed situation may include a motion of
driving the main body in a rotating manner, a backward manner or a
curved manner or rotating a wheel provided in the main body in
order to exit from the sensed situation.
[0029] Furthermore, in an embodiment, the controller may detect at
least one cell in which the main body drives in a non-straight
manner in the first map based on the driving state information, and
find the detected cell and surrounding cells thereof as the
cleaning obstruction area.
[0030] Furthermore, in an embodiment, the second map may include
the remaining areas from which the cleaning obstruction area has
been removed from the first map, or may include only the cleaning
obstruction area in the first map.
[0031] Furthermore, in an embodiment, the controller may control
the driving unit to allow the main body to perform cleaning based
on the second map.
[0032] In addition, a method of operating a robot cleaner according
to an embodiment of the present disclosure may include collecting
driving state information of a main body recorded while cleaning is
performed based on a first map; finding a cleaning obstruction area
in which driving complicated in the first map based on the
collected driving state information; and generating a second map
corresponding to the first map based on the found obstruction
area.
[0033] Furthermore, in an embodiment, the method further includes
performing a cleaning operation of the main body based on the
generated second map.
[0034] In addition, a method of operating a robot cleaner according
to an embodiment of the present disclosure may include storing
driving state information of a main body recorded while performing
a cleaning operation based on a first map; finding a plurality of
cleaning areas corresponding to the first map by dividing them into
a first area and a second area based on the stored driving state;
generating a second map by removing either one of the first area
and the second area from the first map; and performing a cleaning
operation in a varied cleaning mode based on the generated second
map.
[0035] Furthermore, in an embodiment, said generating a second map
may include removing a cleaning obstruction area from the first map
based on the stored driving state information; and setting at least
part of the cleaning area of the first map that is not included in
the second map as a cleaning attention area and adding it to the
second map based on the stored driving state information.
[0036] Furthermore, in an embodiment, said performing a cleaning
operation in a varied cleaning mode may include setting cleaning
areas other than the cleaning attention area in the second map to a
first cleaning mode, and setting the cleaning attention area to a
second cleaning mode different from the first cleaning mode; and
excluding an area of the first map that is not included in the
second map from the cleaning area.
[0037] Furthermore, in an embodiment, the first cleaning mode may
be a quick cleaning mode, and the second cleaning mode may be a
cleaning mode in which at least one of a driving speed of the main
body, a sensitivity level of a sensor provided in the main body,
and a rotation speed of a suction motor provided in the main body
is changed based on driving state information recorded in each
cleaning obstruction area.
[0038] As described above, according to a robot cleaner and an
operation method thereof according to an embodiment of the present
disclosure, it may be possible to generate a map that is robust to
various environmental variables and highly usable without relying
on a sensor. In addition, since it may be possible to find a
cleaning obstruction area from an existing map with only the
driving status information of the robot cleaner without having a
sensor, and a new cleaning mode may be developed and set based
thereon, thereby allowing both cleaning efficiency and cleaning
time to be satisfied.
[0039] For example, it may be possible to quickly clean the
remaining areas except for the cleaning obstruction area that it
takes a long time to clean and causes map lag. Moreover, it may be
possible to reduce the driving speed during the cleaning of the
found cleaning obstruction area, increase the sensitivity level of
the sensor, and increase the suction power, thereby improving the
performing of cleaning. In other words, it may be possible to
shorten the cleaning time and improve the cleaning efficiency at
the same time.
BRIEF DESCRIPTION OF THE DRAWINGS
[0040] FIG. 1 is a perspective view showing an example of a robot
cleaner according to the present disclosure.
[0041] FIG. 2 is a plan view of the robot cleaner illustrated in
FIG. 1.
[0042] FIG. 3 is a side view of the robot cleaner illustrated in
FIG. 1.
[0043] FIG. 4 is a block diagram showing exemplary components of a
robot cleaner according to an embodiment of the present
disclosure.
[0044] FIG. 5 is a block diagram illustrating a main configuration
for generating a map based on driving state information in a robot
cleaner according to an embodiment of the present disclosure.
[0045] FIG. 6 is a flowchart illustrating a method of generating a
map based on driving state information in the robot cleaner
according to an embodiment of the present disclosure.
[0046] FIGS. 7A, 7B, 8A, and 8B are conceptual views illustrating a
process of generating a map based on driving state information and
an example of the generated map in the robot cleaner according to
an embodiment of the present disclosure.
[0047] FIG. 9 is an exemplary flowchart for explaining a method of
performing a cleaning operation using a map generated based on
driving state information in the robot cleaner according to an
embodiment of the present disclosure.
[0048] FIGS. 10, 11, and 12 are conceptual views showing
embodiments related to the flowchart of FIG. 9.
[0049] FIG. 13 is a flowchart for explaining a method of performing
a cleaning operation in different cleaning modes by adding a
cleaning attention area to a map generated based on driving state
information in the robot cleaner according to an embodiment of the
present disclosure.
[0050] FIGS. 14A and 14B are conceptual views for explaining
updating a map from which a cleaning obstruction area is removed
based on a change of driving state information in the robot cleaner
according to an embodiment of the present disclosure.
DETAILED DESCRIPTION OF THE EMBODIMENTS
[0051] Hereinafter, a robot cleaner associated with the present
disclosure will be described in detail with reference to the
accompanying drawings.
[0052] Hereinafter, description will be given in detail of
embodiments disclosed herein. Technical terms used in this
specification are merely used for explaining specific embodiments,
and should not be constructed to limit the scope of the technology
disclosed herein.
[0053] FIG. 1 is a perspective view illustrating an example of a
robot cleaner 100 according to the present disclosure, FIG. 2 is a
plan view of the robot cleaner 100 illustrated in FIG. 1, and FIG.
3 is a side view of the robot cleaner 100 illustrated in FIG.
[0054] In this specification, a mobile robot, a robot cleaner, and
a cleaner that performs autonomous driving may be used in the same
sense. In this specification, a plurality of autonomous cleaners
may include at least part of configurations illustrated in FIGS. 1
to 3.
[0055] Referring to FIGS. 1 through 3, the robot cleaner 100
performs a function of cleaning a floor while driving on a
predetermined area by itself. Cleaning of a floor mentioned here
includes sucking dust (including foreign matter) on the floor or
mopping the floor.
[0056] The robot cleaner 100 may include a cleaner main body 110, a
cleaning unit 120, a sensing unit 130, and a dust container
140.
[0057] The cleaner main body 110 is provided with various
components in addition to a controller (not illustrated) for
controlling the robot cleaner 100. In addition, the cleaner main
body 110 is provided with a wheel unit 111 for the driving of the
robot cleaner 100. The robot cleaner 100 may move forward,
backward, leftward and rightward by the wheel unit 111.
[0058] Referring to FIG. 3, the wheel unit 111 includes main wheels
111a and a sub wheel 111b.
[0059] The main wheels 111a are provided on both sides of the
cleaner main body 110 and configured to be rotatable in one
direction or another direction according to a control signal of the
controller. Each of the main wheels 111a may be configured to be
drivable independently from each other. For example, each main
wheel 111a may be driven by a different motor. Alternatively, each
main wheel 111a may be driven by a plurality of different axes
provided in one motor.
[0060] The sub wheel 111b is configured to support the cleaner body
110 along with the main wheel 111a and assist the driving of the
robot cleaner 100 by the main wheel 111a. The sub wheel 111b may
also be provided on a cleaning unit 120 to be described later.
[0061] The controller is configured to control the driving of the
wheel unit 111 in such a manner that the robot cleaner 100
autonomously drives on the floor.
[0062] Meanwhile, a battery (not shown) for supplying power to the
robot cleaner 100 is mounted on the cleaner body 110. The battery
may be configured to be rechargeable, and configured to be
detachable from a bottom portion of the cleaner body 110.
[0063] In FIG. 1, a cleaning unit 120 may be disposed in a
protruding form from one side of the cleaner main body 110, so as
to suck air containing dust or mop an area. The one side may be a
side where the cleaner main body 110 drives in a forward direction
F, that is, a front side of the cleaner main body 110.
[0064] In this drawing, the cleaning unit 120 is shown having a
shape protruding from one side of the cleaner main body 110 to
front and both left and right sides. Specifically, a front end
portion of the cleaning unit 120 is disposed at a position spaced
forward apart from the one side of the cleaner main body 110, and
left and right end portions of the cleaning unit 120 are disposed
at positions spaced apart from the one side of the cleaner main
body 110 in the right and left directions.
[0065] As the cleaner main body 110 is formed in a circular shape
and both sides of a rear end portion of the cleaning unit 120
protrude from the cleaner main body 110 to both left and right
sides, empty spaces, namely, gaps may be formed between the cleaner
main body 110 and the cleaning unit 120. The vacant space is a
space between both left and right end portions of the cleaner body
110 and both left and right end portions of the cleaning unit 120,
and has a shape recessed in an inward direction of the robot
cleaner 100.
[0066] When an obstacle is caught in the vacant space, the robot
cleaner 100 may be blocked by an obstacle not to move. In order to
prevent this, a cover member 129 may be disposed to cover at least
part of the vacant space.
[0067] The cover member 129 may be provided on the cleaner main
body 110 or the cleaning unit 120. According to the present
embodiment, it is shown that the cover member 129 is formed in a
protruding manner on both sides of a rear end portion of the
cleaning unit 120, and disposed to cover an outer peripheral
surface of the cleaner body 110.
[0068] The cover member 129 is disposed to fill at least part of
the empty space, that is, the empty space between the cleaner main
body 110 and the cleaning unit 120. This may result in realizing a
structure capable of preventing an obstacle from being caught in
the empty space, or to easily escape an obstacle even if the
obstacle is caught in the empty space.
[0069] The cover member 129 protruding from the cleaning unit 120
may be supported on the outer circumferential surface of the
cleaner main body 110.
[0070] The cover member 129 may be supported on a rear portion of
the cleaning unit 120 if the cover member 129 protrudes from the
cleaner main body 110. According to this structure, when the
cleaning unit 120 is impacted due to colliding with an obstacle, a
part of the impact is transferred to the cleaner main body 110 so
as to be dispersed.
[0071] The cleaning unit 120 may be detachably coupled to the
cleaner main body 110. When the cleaning unit 120 is detached from
the cleaner main body 110, a mop module (not shown) may be
detachably coupled to the cleaner main body 110 in place of the
detached cleaning unit 120.
[0072] Accordingly, the user can mount the cleaning unit 120 on the
cleaner main body 110 when the user wishes to remove dust on the
floor, and may mount the mop module on the cleaner main body 110
when the user wants to mop the floor.
[0073] When the cleaning unit 120 is mounted on the cleaner main
body 110, the mounting may be guided by the cover member 129
described above. In other words, as the cover member 129 is
disposed to cover an outer circumferential surface of the cleaner
main body 110 to determine a relative position of the cleaning unit
120 with respect to the cleaner main body 110.
[0074] The cleaning unit 120 may be provided with a castor 123. The
castor 123 is configured to assist the driving of the robot cleaner
100, and also support the robot cleaner 100.
[0075] The cleaner main body 110 is provided with the sensing unit
130. As illustrated, the sensing unit 130 may be disposed on one
side of the cleaner main body 110 where the cleaning unit 120 is
located, that is, on a front side of the cleaner main body 110.
[0076] The sensing unit 130 may be disposed to overlap the cleaning
unit 120 in an up and down direction of the cleaner main body 110.
The sensing unit 130 is disposed at an upper portion of the
cleaning unit 120 to sense an obstacle or geographic feature in
front of the robot cleaner 100 so that the cleaning unit 120
positioned at the forefront of the robot cleaner 100 does not
collide with the obstacle.
[0077] The sensing unit 130 may be configured to additionally
perform another sensing function other than the sensing
function.
[0078] By way of example, the sensing unit 130 may include a camera
131 for acquiring surrounding images. The camera 131 may include a
lens and an image sensor. The camera 131 may convert a surrounding
image of the cleaner main body 110 into an electrical signal that
can be processed by the controller. For example, the camera 131 may
transmit an electrical signal corresponding to an upward image to
the controller. The electrical signal corresponding to the upward
image may be used by the controller to detect the position of the
cleaner main body 110.
[0079] In addition, the sensing unit 130 may detect obstacles such
as walls, furniture, and cliffs on a driving surface or a driving
path of the robot cleaner 100. Also, the sensing unit 130 may sense
presence of a docking device that performs battery charging. Also,
the sensing unit 130 may detect ceiling information so as to map a
driving area or a cleaning area of the robot cleaner 100.
[0080] The cleaner main body 110 is provided with a dust container
140 detachably coupled thereto for separating and collecting dust
from sucked air.
[0081] The dust container 140 is provided with a dust container
cover 150 which covers the dust container 140. In an embodiment,
the dust container cover 150 may be coupled to the cleaner main
body 110 by a hinge to be rotatable. The dust container cover 150
may be fixed to the dust container 140 or the cleaner main body 110
to keep covering an upper surface of the dust container 140. The
dust container 140 may be prevented from being separated from the
cleaner main body 110 by the dust container cover 150 when the dust
container cover 150 is disposed to cover the upper surface of the
dust container 140.
[0082] A part of the dust container 140 may be accommodated in a
dust container accommodating portion and another part of the dust
container 140 protrudes toward the rear of the cleaner main body
110 (i.e., a reverse direction R opposite to a forward direction
F).
[0083] The dust container 140 is provided with an inlet through
which air containing dust is introduced and an outlet through which
air separated from dust is discharged. The inlet and the outlet
communicate with each other through an opening 155 formed through
an inner wall of the cleaner main body 110 when the dust container
140 is mounted on the cleaner main body 110. Thus, an intake
passage and an exhaust passage inside the cleaner main body 110 may
be formed.
[0084] According to such connection, air containing dust introduced
through the cleaning unit 120 flows into the dust container 140
through the intake passage inside the cleaner main body 110 and the
air is separated from the dust while passing through a filter and
cyclone of the dust container 140. Dust is collected in the dust
box 140, and air is discharged from the dust box 140 and then
discharged to the outside through the discharge port 112 in the
cleaner body 110 and finally through the discharge port 112.
[0085] An embodiment related to the components of the robot cleaner
100 will be described below with reference to FIG. 4.
[0086] The robot cleaner 100 or the mobile robot according to an
embodiment of the present disclosure may include a communication
unit 1100, an input unit 1200, a driving unit 1300, a sensing unit
1400, an output unit 1500, a power supply unit 1600, a memory 1700,
a controller 1800, and a cleaning unit 1900, or a combination
thereof.
[0087] Here, it is needless to say that the components shown in
FIG. 4 are not essential, and thus a robot cleaner having more or
fewer components than shown in FIG. 4 may be implemented. Also, as
described above, each of a plurality of robot cleaners described in
the present disclosure may equally include only some of components
to be described below. In other words, a plurality of robot
cleaners may include different components.
[0088] Hereinafter, each component will be described.
[0089] First, the power supply unit 1600 includes a battery that
can be charged by an external commercial power supply, and supplies
power to the mobile robot. The power supply unit 1600 supplies
driving power to each of the components included in the mobile
robot to supply operating power required for the mobile robot to
drive or perform a specific function.
[0090] Here, the controller 1800 may sense the remaining power of
the battery, and control the battery 1800 to move power to a
charging base connected to the external commercial power source
when the remaining power is insufficient, and thus a charge current
may be supplied from the charging base to charge the battery. The
battery may be connected to a battery sensing unit, and a battery
remaining amount and a charging state may be delivered to the
controller 1800. The output unit 1500 may display the remaining
battery level under the control of the controller.
[0091] The battery may be located in a lower portion of the center
of the robot cleaner or may be located at either one of the left
and right sides. In the latter case, the mobile robot may further
include a balance weight for eliminating a weight bias of the
battery.
[0092] The controller 1800 performs a role of processing
information based on an artificial intelligence technology and may
include at least one module for performing at least one of learning
of information, inference of information, perception of
information, and processing of a natural language.
[0093] The controller 1800 may use a machine learning technology to
perform at least one of learning, inference and processing of a
large amount of information (big data), such as information stored
in the cleaner, environment information around the cleaner,
information stored in a communicable external storage, and the
like. Furthermore, the controller 1800 may predict (or infer) at
least one executable operation of the cleaner based on information
learned using the machine learning technology, and control the
cleaner to execute the most feasible operation among the at least
one predicted operation.
[0094] The machine learning technology is a technology that
collects and learns a large amount of information based on at least
one algorithm, and determines and predicts information based on the
learned information. The learning of information is an operation of
grasping characteristics of information, rules and judgment
criteria, quantifying a relation between information and
information, and predicting new data using the quantified
patterns.
[0095] Algorithms used by the machine learning technology may be
algorithms based on statistics, for example, a decision tree that
uses a tree structure type as a prediction model, an artificial
neural network that mimics neural network structures and functions
of living creatures, genetic programming based on biological
evolutionary algorithms, clustering of distributing observed
examples to a subset of clusters, a Monte Carlo method of computing
function values as probability using randomly-extracted random
numbers, and the like.
[0096] As one field of the machine learning technology, deep
learning is a technology of performing at least one of learning,
determining, and processing information using a deep neural network
(DNN) algorithm. The deep neural network (DNN) may have a structure
of linking layers and transferring data between the layers. This
deep learning technology may be employed to learn a vast amount of
information through the deep neural network (DNN) using a graphic
processing unit (GPU) optimized for parallel computing.
[0097] The controller 1800 may use training data stored in an
external server or a memory, and may include a learning engine for
detecting a characteristic for recognizing a predetermined object.
Here, characteristics for recognizing an object may include the
size, shape, and shade of the object.
[0098] Specifically, when the controller 1800 inputs a part of
images acquired through the camera provided on the cleaner into the
learning engine, the learning engine may recognize at least one
object or organism included in the input images.
[0099] When the learning engine is applied to driving of the
cleaner, the controller 1800 can recognize whether or not an
obstacle such as a chair leg, a fan, and a specific shape of
balcony gap, which obstruct the running of the cleaner, exists
around the cleaner. This may result in enhancing efficiency and
reliability of the driving of the cleaner.
[0100] On the other hand, the learning engine may be mounted on the
controller 1800 or on an external server. When the learning engine
is mounted on an external server, the controller 1800 may control
the communication unit 1100 to transmit at least one image to be
analyzed, to the external server.
[0101] The external server may input the image transmitted from the
cleaner into the learning engine and thus recognize at least one
object or organism included in the image. In addition, the external
server may transmit information related to the recognition result
back to the cleaner. In this case, the information related to the
recognition result may include information related to the number of
objects included in the image to be analyzed and a name of each
object.
[0102] On the other hand, the driving unit 1300 may include a
motor, and operate the motor to bidirectionally rotate left and
right main wheels, so that the main body can rotate or move. At
this time, the left and right main wheels may be independently
moved. The driving unit 1300 may advance the main body of the
mobile robot forward, backward, left, right, curvedly, or in
place.
[0103] Meanwhile, the input unit 1200 receives various control
commands for the robot cleaner from the user. The input unit 1200
may include one or more buttons, for example, the input unit 1200
may include an OK button, a set button, and the like. The OK button
is a button for receiving a command for confirming sensing
information, obstacle information, position information, and map
information from the user, and the set button is a button for
receiving a command for setting the information from the user.
[0104] In addition, the input unit 1200 may include an input reset
button for canceling a previous user input and receiving a user
input again, a delete button for deleting a preset user input, a
button for setting or changing an operation mode, a button for
receiving a command to be restored to the charging base, and the
like.
[0105] Furthermore, the input unit 1200, such as a hard key, a soft
key, a touch pad, or the like, may be installed on a upper portion
of the mobile robot. In addition, the input unit 1200 may have a
form of a touch screen along with the output unit 1500.
[0106] On the other hand, the output unit 1500 may be installed on
an upper portion of the mobile robot. Of course, the installation
location and installation type may vary. For example, the output
unit 1500 may display a battery state, a driving mode, and the like
on the screen.
[0107] In addition, the output unit 1500 may output state
information inside the mobile robot detected by the sensing unit
1400, for example, a current state of each configuration included
in the mobile robot. Moreover, the output unit 1500 may display
external state information, obstacle information, position
information, map information, and the like detected by the sensing
unit 1400 on the screen. The output unit 1500 may be formed with
any one of a light emitting diode (LED), a liquid crystal display
(LCD), a plasma display panel, and an organic light emitting diode
(OLED).
[0108] The output unit 1500 may further include a sound output
device for audibly outputting an operation process or an operation
result of the mobile robot performed by the controller 1800. For
example, the output unit 1500 may output a warning sound to the
outside in accordance with a warning signal generated by the
controller 1800.
[0109] In this case, the audio output module (not shown) may be
means, such as a beeper, a speaker or the like for outputting
sounds, and the output unit 1500 may output sounds to the outside
through the audio output module using audio data or message data
having a predetermined pattern stored in the memory 1700.
[0110] Accordingly, the mobile robot according to an embodiment of
the present disclosure may output environment information on a
driving area on the screen or output it as sound. According to
another embodiment, the mobile robot may transmit map information
or environment information to a terminal device through the
communication unit 1100 to output a screen or sound to be output
through the output unit 1500.
[0111] The memory 1700 stores a control program for controlling or
driving the robot cleaner and the resultant data. The memory 1700
may store audio information, image information, obstacle
information, position information, map information, and the like.
Furthermore, the memory 1700 may store information related to a
driving pattern.
[0112] The memory 1700 mainly uses a nonvolatile memory. Here, the
non-volatile memory (NVM, NVRAM) is a storage device capable of
continuously storing information even when power is not supplied
thereto, and for an example, the non-volatile memory may be a ROM,
a flash memory, a magnetic computer storage device (e.g., a hard
disk, a diskette drive, a magnetic tape), an optical disk drive, a
magnetic RAM, a PRAM, and the like.
[0113] Meanwhile, the sensing unit 1400 may include at least one of
an external signal detection sensor, a front detection sensor, a
cliff detection sensor, a two-dimensional camera sensor, and a
three-dimensional camera sensor.
[0114] The external signal detection sensor may sense an external
signal of the mobile robot. The external signal detection sensor
may be, for example, an infrared ray sensor, an ultrasonic sensor,
a radio frequency (RF) sensor, or the like.
[0115] The mobile robot may receive a guide signal generated by the
charging base using the external signal detection sensor to check
the position and direction of the charging base. At this time, the
charging base may transmit a guide signal indicating the direction
and the distance to allow the mobile robot to return. In other
words, the mobile robot may receive a signal transmitted from the
charging base to determine a current position, set a moving
direction, and return to the charging base.
[0116] On the other hand, the front detection sensor may be
installed at predetermined intervals at a front side of the mobile
robot, specifically along a lateral outer circumferential surface
of the mobile robot. The front sensor is located on at least one
side surface of the mobile robot to detect an obstacle in front of
the mobile robot. The front sensor may detect an object, especially
an obstacle, existing in a moving direction of the mobile robot and
transmit detection information to the controller 1800. In other
words, the front sensor may detect protrusions on the moving path
of the mobile robot, household appliances, furniture, walls, wall
corners, and the like, and transmit the information to the
controller 1800.
[0117] For example, the frontal sensor may be an infrared ray (IR)
sensor, an ultrasonic sensor, an RF sensor, a geomagnetic sensor,
or the like, and the mobile robot may use one type of sensor as the
front sensor or two or more types of sensors if necessary.
[0118] For an example, the ultrasonic sensors may be mainly used to
sense a distant obstacle in general. The ultrasonic sensor may
include a transmitter and a receiver, and the controller 1800 may
determine whether or not there exists an obstacle based on whether
or not ultrasonic waves radiated through the transmitter is
reflected by the obstacle or the like and received at the receiver,
and calculate a distance to the obstacle using the ultrasonic
emission time and ultrasonic reception time.
[0119] Furthermore, the controller 1800 may compare ultrasonic
waves emitted from the transmitter and ultrasonic waves received at
the receiver to detect information related to a size of the
obstacle. For example, the controller 1800 may determine that the
larger the obstacle is, the more ultrasonic waves are received at
the receiver.
[0120] In one embodiment, a plurality of (for example, five)
ultrasonic sensors may be provided along a lateral outer
circumferential surface at a front side of the mobile robot. At
this time, the ultrasonic sensors may preferably be installed on
the front surface of the mobile robot in a manner that the
transmitter and the receiver are alternately arranged.
[0121] In other words, the transmitters may be spaced apart from
the front center of the main body to the left and right sides, and
one or two (or more) transmitters may be disposed between the
receivers to form a receiving area of ultrasonic signals reflected
from an obstacle or the like. With this arrangement, the receiving
area may be expanded while reducing the number of sensors. A
transmission angle of ultrasonic waves may maintain a range of
angles that do not affect different signals to prevent a crosstalk
phenomenon. Furthermore, the receiving sensitivities of the
receivers may be set to be different from each other.
[0122] In addition, the ultrasonic sensor may be installed upward
by a predetermined angle so that the ultrasonic waves emitted from
the ultrasonic sensor are output upward. In this instance, the
ultrasonic sensor may further include a predetermined blocking
member to prevent the ultrasonic waves from being radiated
downward.
[0123] On the other hand, as described above, the front sensor may
be implemented by using two or more types of sensors together, and
thus the front sensor may use any one of an IR sensor, an
ultrasonic sensor, an RF sensor and the like.
[0124] For example, the front detection sensor may include an
infrared sensor as a different type of sensor other than the
ultrasonic sensor.
[0125] The infrared sensor may be installed on an outer
circumferential surface of the mobile robot together with the
ultrasonic sensor. The infrared sensor may also sense an obstacle
existing at the front or the side to transmit obstacle information
to the controller 1800. In other words, the infrared sensor may
sense a protrusion on the moving path of the mobile robot, a
household appliance, a furniture, a wall, a wall corner, and the
like, and transmit the information to the controller 1800.
Therefore, the mobile robot may move within a specific area without
collision with the obstacle.
[0126] On the other hand, a cliff detection sensor (or cliff
sensor) may sense an obstacle on the floor supporting the main body
of the mobile robot mainly using various types of optical
sensors.
[0127] In other words, the cliff detection sensor may be installed
on a rear surface of the bottom mobile robot, but may of course be
installed in a different position depending on the type of the
mobile robot. The cliff detection sensor is a sensor located on a
back surface of the mobile robot to sense an obstacle on the floor,
and the cliff detection sensor may be an infrared sensor, an
ultrasonic sensor, an RF sensor, a PSD (Position Sensitive
Detector) sensor, or the like, which is provided with a transmitter
and a receiver such as the obstacle detection sensor.
[0128] For an example, any one of the cliff detection sensors may
be installed in front of the mobile robot, and the other two cliff
detection sensors may be installed relatively behind.
[0129] For example, the cliff detection sensor may be a PSD sensor,
but may also be configured with a plurality of different kinds of
sensors.
[0130] The PSD sensor detects a short and long distance position of
incident light with one p-n junction using a semiconductor surface
resistance. The PSD sensor includes a one-dimensional PSD sensor
that detects light only in one axial direction, and a
two-dimensional PSD sensor that detects a light position on a
plane. Both of the PSD sensors may have a pin photodiode structure.
The PSD sensor is a type of infrared sensor that uses infrared rays
to transmit infrared rays and then measure an angle of infrared
rays reflected from and returned back to an obstacle so as to
measure a distance. In other words, the PSD sensor calculates a
distance from the obstacle by using the triangulation method.
[0131] The PSD sensor includes a light emitter that emits infrared
rays to an obstacle and a light receiver that receives infrared
rays that are reflected and returned from the obstacle, and is
configured typically as a module type. When an obstacle is sensed
using the PSD sensor, a stable measurement value may be obtained
irrespective of the reflectance and the color difference of the
obstacle.
[0132] The cleaning unit 1900 cleans a designated cleaning area
according to a control command transmitted from the controller
1800. The cleaning unit 1900 scatters dust in the vicinity through
a brush (not shown) that scatters dust in a designated cleaning
area, and then drives the suction fan and the suction motor to suck
the scattered dust. In addition, the cleaning unit 1900 may perform
mopping in a designated cleaning area according to the replacement
of the configuration.
[0133] Furthermore, the controller 1800 may measure an infrared ray
angle between a light signal of infrared ray emitted by the cliff
detection sensor toward the ground and a reflection signal
reflected and received from an obstacle, so as to detect a cliff
and analyze a depth of the cliff.
[0134] Meanwhile, the controller 1800 may determine whether to pass
a cliff or not according to a ground state of the detected cliff by
using the cliff detection sensor, and decide whether to pass the
cliff or not according to the determination result. For example,
the controller 1800 determines presence or non-presence of a cliff
and a depth of the cliff through the cliff sensor, and then allows
the mobile robot to pass through the cliff only when a reflection
signal is detected through the cliff sensor.
[0135] As another example, the controller 1800 may also determine
lifting of the mobile robot using the cliff sensor.
[0136] On the other hand, the two-dimensional camera sensor is
provided on one side of the mobile robot to acquire image
information related to the surroundings of the main body during
movement.
[0137] An optical flow sensor converts a downward image input from
an image sensor provided in the sensor to generate image data in a
predetermined format. The generated image data may be stored in the
memory 1700.
[0138] Furthermore, one or more light sources may be installed
adjacent to the optical flow sensor. The one or more light sources
irradiate light to a predetermined area of the bottom surface
captured by the image sensor. In other words, when the mobile robot
moves in a specific area along the bottom surface, a predetermined
distance is maintained between the image sensor and the bottom
surface when the bottom surface is flat. On the other hand, when
the mobile robot moves on a bottom surface having a nonuniform
surface, the robot moves away from the bottom surface by more than
a predetermined distance due to the irregularities of the bottom
surface and obstacles. At this time, the one or more light sources
may be controlled by the controller 1800 to adjust an amount of
light to be irradiated. The light source may be a light emitting
device capable of controlling the amount of light, for example, a
light emitting diode (LED) or the like.
[0139] Using the optical flow sensor, the controller 1800 may
detect a position of the mobile robot irrespective of the slip of
the mobile robot. The controller 1800 may compare and analyze the
image data captured by the optical flow sensor over time to
calculate the moving distance and the moving direction, and
calculate the position of the mobile robot on the basis of the
moving distance and the moving direction. Using image information
on a bottom side of the mobile robot using the optical flow sensor,
the controller 1800 may perform slip-resistant correction on the
position of the mobile robot calculated by another device.
[0140] The three-dimensional camera sensor may be attached to one
side or a part of the main body of the mobile robot to generate
three-dimensional coordinate information related to the
surroundings of the main body.
[0141] In other words, the three-dimensional camera sensor may be a
3D depth camera that calculates a near and far distance of the
mobile robot and an object to be captured.
[0142] Specifically, the three-dimensional camera sensor may
capture a two-dimensional image related to the surroundings of the
main body, and generate a plurality of three-dimensional coordinate
information corresponding to the captured two-dimensional
image.
[0143] In an embodiment, the three-dimensional camera sensor may
include two or more cameras that acquire a conventional
two-dimensional image, and may be formed in a stereo vision manner
to combine two or more images obtained from the two or more cameras
so as to generate three-dimensional coordinate information.
[0144] Specifically, the three-dimensional camera sensor according
to the embodiment may include a first pattern irradiation unit for
irradiating light with a first pattern in a downward direction
toward the front of the main body, and a second pattern irradiation
unit for irradiating the light with a second pattern in an upward
direction toward the front of the main body, and an image
acquisition unit for acquiring an image in front of the main body.
As a result, the image acquisition unit may acquire an image of an
area where light of the first pattern and light of the second
pattern are incident.
[0145] In another embodiment, the three-dimensional camera sensor
may include an infrared ray pattern emission unit for irradiating
an infrared ray pattern together with a single camera, and capture
the shape of the infrared ray pattern irradiated from the infrared
ray pattern emission unit onto the object to be captured, thereby
measuring a distance between the sensor and the object to be
captured. Such a three-dimensional camera sensor may be an IR
(infrared) type three-dimensional camera sensor.
[0146] In still another embodiment, the three-dimensional camera
sensor may include a light emitting unit that emits light together
with a single camera, receive a part of laser emitted from the
light emitting unit reflected from the object to be captured, and
analyze the received laser, thereby measuring a distance between
the three-dimensional camera sensor and the object to be captured.
The three-dimensional camera sensor may be a time-of-flight (TOF)
type three-dimensional camera sensor.
[0147] Specifically, the laser of the above-described
three-dimensional camera sensor is configured to irradiate a laser
beam in the form of extending in at least one direction. In one
example, the three-dimensional camera sensor may include first and
second lasers, wherein the first laser irradiates a linear shaped
laser intersecting each other, and the second laser irradiates a
single linear shaped laser. According to this, the lowermost laser
is used to sense obstacles in the bottom portion, the uppermost
laser is used to sense obstacles in the upper portion, and the
intermediate laser between the lowermost laser and the uppermost
laser is used to sense obstacles in the middle portion.
[0148] On the other hand, the communication unit 1100 is connected
to a terminal device and/or another device (also referred to as
"home appliance" herein) through one of wired, wireless and
satellite communication methods, so as to transmit and receive
signals and data.
[0149] The communication unit 1100 may transmit and receive data
with another located in a specific area. Here, the another device
may be any device capable of connecting to a network to transmit
and receive data, and for example, the device may be an air
conditioner, a heating device, an air purification device, a lamp,
a TV, an automobile, or the like. The another device may also be a
device for controlling a door, a window, a water supply valve, a
gas valve, or the like. The another device may be a sensor for
sensing temperature, humidity, air pressure, gas, or the like.
[0150] Further, the communication unit 1100 may communicate with
another robot cleaner 100 located in a specific area or within a
predetermined range.
[0151] On the other hand, the robot cleaner 100 according to the
present disclosure may generate a map that is robust to various
environmental variables and highly usable without relying on a
sensor. Furthermore, while the cleaning operation is performed
based on an existing map, a cleaning obstruction area in which
driving is complicated may be distinguished and found based on an
actual driving state of the robot cleaner 100. Moreover, based on
the found cleaning obstruction area, a new map may be generated
and/or a new cleaning mode may be set.
[0152] Hereinafter, a main configuration of the robot cleaner 100
for generating a new map based on driving state information will be
described with reference to FIG. 5.
[0153] In addition to the configuration described with reference to
FIGS. 1 to 4, the robot cleaner 100 according to the present
disclosure may further include a driving state information
collection unit 510, a cleaning obstruction area finding unit 520,
and a variable map generation unit 530.
[0154] Furthermore, an operation by the driving state information
collection unit 510, the cleaning obstruction area finding unit
520, and the variable map generation unit 530 may be performed by
the controller 1800 (or hardware process) of FIG. 4.
[0155] Specifically, the driving state information collection unit
510 collects driving state information for each area or cells
constituting each region while the robot cleaner 100 cleans a
designated cleaning area.
[0156] Here, the driving state information includes all information
on the motion of the driving unit 1300 corresponding to a situation
sensed through a sensor provided in the robot cleaner 100 while
performing a cleaning operation based on an existing map
(hereinafter, referred to as a "first map").
[0157] Specifically, the sensed situation may include a case where
the robot cleaner 100 senses an obstacle existing in a driving
path, senses a ground state of the driving path, or senses a wheel
falling off of the robot cleaner body in a cleaning area
corresponding to the first map.
[0158] Furthermore, the sensed situation may include a case where
that the robot cleaner body senses a collision, senses a wheel slip
of the body, senses a wall following, senses a set virtual wall,
senses a cliff, or senses a learned trap.
[0159] In order to sense such a situation, the robot cleaner 100
may include at least one sensor. For example, the robot cleaner 100
may include a 2D/3D camera sensor, a front sensor, a cliff sensor,
an external signal detection sensor (infrared, ultrasonic, RF, UWB
sensor, etc.), a collision sensor (/bumper), a geomagnetic sensor,
a bumper sensor, a floor sensor, and the like.
[0160] In addition, in order to detect such a situation, the robot
cleaner 100 may communicate with a server (not shown) or may access
its own memory 1700.
[0161] In this case, the robot cleaner may detect information on a
learned trap area or setting information by an input based on
training data stored in the server or memory 1700.
[0162] On the other hand, the present invention does not rely on a
sensor to find a cleaning obstruction area in which driving is
complicated. Therefore, there is no limitation on the type and
number of sensors of the robot cleaner 100 that must be provided
therein in order to sense the above-described situation.
[0163] Specifically, even in the same cleaning area, the driving
state of the robot cleaner may vary depending on the structure,
performance, and/or the number of sensors provided therein. For
example, a robot cleaner may be driven in a straight manner, but
another robot cleaner may cause wheel slip in the relevant
area/cell.
[0164] The motion of the driving unit 1300 corresponding to the
sensed situation as described above may include a motion of driving
the robot cleaner body in a rotating manner, a backward manner or a
curved line or rotating a wheel provided in the robot cleaner body
in order to exit from the sensed situation.
[0165] For example, when a wheel of the driving unit 1300 is
rotated several times to exit the relevant area/point in a
situation in which wheel slip is found, it may be recognized as a
motion of the driving unit 1300 corresponding to the sensed
situation.
[0166] Furthermore, when temporarily escaping from a predetermined
driving path to avoid an obstacle in a situation where the obstacle
is sensed in the front, it may be recognized as a motion of the
driving unit 1300 corresponding to the sensed situation.
[0167] Accordingly, information on the motion of the driving unit
includes information on a number of rotations of the wheel, a
direction of rotation of the wheel, and a number of changes in the
rotation direction of the driving unit 1300.
[0168] A case where the robot cleaner body is driven to rotate,
move backward, or move in a curved manner, or a wheel provided in
the robot cleaner body is rotated in order to be driven according
to a predetermined driving path may be excluded from the
information on the motion of the driving unit.
[0169] For example, a case where the robot cleaner 100 rotates the
main body or a wheel provided in the main body in order to change a
driving line according to a zigzag cleaning mode may be excluded
from information on the motion of the driving unit described
above.
[0170] The cleaning obstruction area finding unit 520 finds a
cleaning obstruction area in which driving is complicated from the
first map based on driving status information collected by the
driving status information collection unit 510.
[0171] Here, the cleaning obstruction area in which driving is
complicated refers to an area in which a response motion of the
driving unit 1300 has been generated based on a situation sensed
based on a sensor provided in the robot cleaner 100 and/or access
information.
[0172] The response motion, which is an operation of the driving
unit 1300 to overcome the sensed situation, may include a motion of
performing, for example, rotation, backward movement,
change-of-direction, stop, change-of-speed, rotation-in-place,
riding, and the like.
[0173] Therefore, a case where the robot cleaner 100 drives in a
straight manner or a case where the robot cleaner 100 drives on a
driving path determined based on the first map may be excluded from
the cleaning obstruction area even when the robot cleaner 100
performs rotation, backward movement, change-of-direction, and the
like.
[0174] In addition, the cleaning obstruction area finding unit 520
may detect at least one cell in which the main body drives in a
non-straight manner from the first map based on the driving state
information by the driving unit 1300 of the robot cleaner.
Moreover, an area including the detected cell and surrounding cells
thereof may be found as a cleaning obstruction area.
[0175] The variable map generation unit 530 generates a second map
corresponding to the first map based on the cleaning obstruction
area detected by the cleaning obstruction area finding unit
520.
[0176] Specifically, the second map may be generated by removing
all of the found cleaning obstruction areas from the first map.
Furthermore, the second map may be generated by including only the
found cleaning obstruction area as a cleaning area.
[0177] In addition, the second map may be generated by maintaining
only some of the found cleaning obstruction areas in the first map
that satisfy a preset condition and removing the other areas. In
this case, the second map is generated to allow the robot cleaner
100 to distinguish and recognize the added cleaning obstruction
areas and other cleaning areas.
[0178] When the second map is generated in this way, the robot
cleaner 100 may now perform a cleaning operation using the second
map.
[0179] For example, cleaning may be performed by rapidly driving
straight ahead only the remaining areas except for the cleaning
obstruction areas using the second map. Furthermore, for example,
cleaning may be performed while changing the cleaning mode in the
cleaning obstruction areas using the second map. Specific
embodiments of the cleaning operation using the second map will be
described in more detail below.
[0180] Hereinafter, FIG. 6 is a flowchart for explaining a method
of generating a map based on driving state information in the robot
cleaner 100 according to the present disclosure.
[0181] Referring to FIG. 6, first, while the main body of the robot
cleaner 1000 performs a cleaning operation based on the first map,
driving state information on the cleaning areas of the first map is
collected (510).
[0182] Here, the first map may be a map generated by the robot
cleaner 100 based on information obtained by initially searching
for unknown areas, for example, an obstacle map. In addition, the
first map may be a learning map in which the robot cleaner 100
reflects a path plan established for each cleaning area using the
map and learned data on the map.
[0183] Furthermore, the collection of the driving state information
may be collected in a cell unit for each of a plurality of cells
constituting the first map. The first map may be a grid map
composed of a plurality of cells.
[0184] Whenever the robot cleaner 100 passes through one cell
constituting the first map, driving state information is recorded
by the driving unit 1300 of the robot cleaner 100.
[0185] Specifically, it may be recorded whether the robot cleaner
100 has driven in a straight or non-straight manner in the relevant
cell. In addition, when the robot cleaner 100 drives in a
non-straight manner in the relevant cell, rotates in place, or
changes the driving direction, it may be obtained whether the
motion corresponds to a predetermined driving path.
[0186] In a case where the main body drives and passes through a
specific cell in a non-straight manner and the path does not
correspond to a predetermined driving path, the controller of the
robot cleaner 100 recognizes it as a motion of the driving unit
1300 corresponding to a specific situation, that is, a response
motion.
[0187] The collection of such driving state information is ended
upon completion of cleaning for the cleaning areas of the first
map.
[0188] Next, the robot cleaner 1000 finds a cleaning obstruction
area in which driving is complicated from the first map based on
the collected driving state information (S20).
[0189] Here, the cleaning obstruction area refers to an area in
which a response motion of the driving unit 1300 has been generated
based on a situation sensed based on a sensor provided in the robot
cleaner 100 and/or information accessed by the robot cleaner.
[0190] Alternatively, the cleaning obstruction area refers to an
area including cells that do not correspond to a predetermined
driving path while the driving unit of the robot cleaner 100 drives
in a non-straight manner based on the collected driving state
information.
[0191] The controller of the robot cleaner 100 may attach an
adjacent cell in which a response motion by the driving unit 1300
has been generated and set it as a cleaning obstruction area.
Accordingly, there may be one or a plurality of cleaning areas in
the first map, and since driving state information is collected in
a cell unit, the size or shape may be different from each
other.
[0192] An important point here is that the cleaning obstruction
area is found not based on information sensed through a sensor, but
based on information on a driving state of the robot cleaner
100.
[0193] Therefore, when the robot cleaner types are different,
motions of the driving unit corresponding to the sensed situations
may be different from each other, and thus the number, position,
size, and shape of the found cleaning obstruction areas may be
different.
[0194] Next, the robot cleaner 100 may generate a second map
corresponding to the first map based on the found cleaning
obstruction areas (S30).
[0195] Specifically, the second map may be generated by removing
all of the found cleaning obstruction areas from the first map.
Furthermore, the second map may be generated by including only the
found cleaning obstruction area as a cleaning area.
[0196] In addition, the second map may be generated by maintaining
only some of the found cleaning obstruction areas in the first map
that satisfy a preset condition and removing the other areas. In
this case, the second map is generated to allow the robot cleaner
100 to distinguish and recognize the added cleaning obstruction
areas and other cleaning areas.
[0197] The generated second map may be stored together with the
first map in a memory of the robot cleaner 100 or in a server
capable of communicating therewith. In addition, if necessary, the
robot cleaner 100 may call only one of the first map and the second
map, or call both the first map and the second map and use them
during a cleaning operation.
[0198] As described above, in the present disclosure, it may be
possible to generate a map that is robust to various environmental
variables and highly usable without relying on a sensor of a robot
cleaner. In addition, a cleaning obstruction area that takes a long
time to clean and is complicated to drive may be found using only
the driving state information of the robot cleaner based on the map
to reflect it on a new map.
[0199] Hereinafter, FIGS. 7A and 7B are exemplary conceptual views
for finding cleaning obstruction areas, and FIGS. 8A and 8B
illustrate an example of a second map generated based on the found
cleaning obstruction areas.
[0200] First, a method of finding cleaning obstruction areas from a
first map will be described in detail with reference to FIGS. 7A
and 7B.
[0201] As illustrated in FIG. 7A, the first map 701 may be used for
the robot cleaner 100 to drive a cleaning area on a zigzag driving
path.
[0202] However, the actual driving path 711 of the robot cleaner
100 based on the first map 701 attempts driving different from the
zigzag driving path when a specific situation is detected. In other
words, the robot cleaner 100 drives in a non-straight manner in a
cleaning area, continuously rotates the wheel to exit, or performs
a response motion that forms a complicated path.
[0203] The determination as to whether the response motion has been
performed is made for each of a plurality of cells constituting the
first map 701 in a cell unit.
[0204] The robot cleaner stores the driving state of the driving
unit 1300 each time it passes through each cell until the entire
area of the first map 701 is covered.
[0205] Here, the driving state includes both a case where a
response motion is not performed to drive in a straight manner and
a case where a response motion is performed.
[0206] Specifically, while a specific situation is not sensed, the
robot cleaner drives on a zigzag driving path in the cleaning area
of the first map 701. At this time, the robot cleaner passes
through a cell 721 in a straight manner, as illustrated in FIG. 7B.
This driving state information may be classified into a first
group.
[0207] Then, when a first situation in which cleaning under a sofa
needs to be cleaned (must be driven by avoiding a plurality of sofa
legs) is sensed, a first response motion 10a corresponding to the
sensed first situation is generated In this case, the robot cleaner
passes through a cell 722 in a non-straight manner, as illustrated
in FIG. 7B. This driving state information may be classified into a
second group.
[0208] Further, for example, when a second situation in which the
ground state is uneven is sensed, a second response motion 10b
corresponding to the sensed second situation is generated.
[0209] In addition, when a third situation is sensed by detection
of an obstacle, for example, a third response motion 10c
corresponding to the sensed third situation may be generated.
[0210] Further, for example, when a fourth situation according to a
wheel slip of the robot cleaner or a virtual wall or a learned trap
is sensed, a fourth response motion 10d corresponding to the sensed
fourth situation may be generated.
[0211] At this time, driving state information corresponding to
cells that have passed through non-straight driving by the second
response motion 10b, the third response motion 10c, and the fourth
response motion 10d may be classified into the second group.
[0212] However, driving information for each of the first response
motions 10a to fourth response motions 10d, for example, driving
information regarding the number of rotations of the wheel, the
direction of rotation of the wheel, and the number of changes in
the rotation direction of the driving unit 1300 is also
recorded.
[0213] Therefore, when the driving of the robot cleaner based on
the first map 701 is completed, the controller of the robot cleaner
may not only distinguish between an area in which the response
motion has been generated and an area that has not been generated,
but also distinguish and recognize a plurality of areas in which
the first response motion 10a to the fourth response motion 10d
have been generated, from each other.
[0214] Furthermore, each of the first response motion 10a to the
fourth response motion 10d does not denote one driving motion for
any one situation.
[0215] For example, for the fourth response motion corresponding to
the above-described fourth situation, various response motions such
as wheel rotation->backward movement->forward
movement->wheel rotation may be generated multiple times, and
the fourth response motion includes all the motions of the driving
unit.
[0216] In addition, in the present disclosure, there is no
particular limitation on elements for sensing the above-described
first to fourth situations. In other words, a sensor provided in
the robot cleaner may be used, or a server in connection with the
robot cleaner may be used.
[0217] For example, the wheel slip may be sensed based on the
number of rotations and movement displacement of the wheel of the
robot cleaner. The virtual wall may be sensed through a magnetic
sensor provided in the robot cleaner. Furthermore, the learned trap
may be sensed by accessing information stored in the memory of the
robot cleaner or a server in connection therewith.
[0218] In addition, even when the first to fourth situations are
sensed in the same manner, a difference may be generated in the
response motion according to the performance/specification of the
robot cleaner. Therefore, finally, the size, shape, and number of
the cleaning obstruction areas may vary for each robot cleaner to
be used.
[0219] Furthermore, even when the performance/specifications of the
robot cleaner are the same, some of the first to fourth situations
may not be sensed according to the learned data. For example, since
a robot cleaner for which trap learning has not been performed is
unable to sense the fourth situation, the fourth response motion
10d corresponding to the fourth situation is not generated.
[0220] In this way, when the robot cleaner covers the entire area
of the first map 701, the cleaning obstacle areas R1, R2, R3, R4
may be detected from the first map 701 based on the driving state
information classified into the first group and the second
group.
[0221] At this time, the detected cleaning obstruction areas R1,
R2, R3, and R4 may partially include cells corresponding to the
first group and/or cells without having driving state
information.
[0222] For example, when the stored driving state information is
non-straight driving for a first cell->straight driving for a
second cell->non-straight driving for a third cell in a
longitudinal direction, all the first, second and third cells may
be detected as cleaning obstruction areas.
[0223] In addition, in an example, the cleaning obstruction areas
R1, R2, R3, and R4 may be detected in a predetermined shape, for
example, a rectangle. Accordingly, the shape of the area 10d in
which the fourth response motion corresponding to the learned trap
has been generated and the shape of the relevant cleaning
obstruction area R4 may be different from each other.
[0224] Next, with reference to FIGS. 8A and 8B, a method of
generating a second map based on the cleaning obstruction regions
R1, R2, R3, and R4 will be described in detail.
[0225] For an example, as described in FIGS. 7A and 7B, when the
cleaning obstruction areas R1, R2, R3, and R4 are detected from the
first map, a second map 801 from which the cleaning obstruction
areas R1, R2, R3, and R4 have been removed from the first map may
be generated as illustrated in FIG. 8A.
[0226] The second map 801 may consist of only driving state
information belonging to the first group, that is, only cells in
which the robot cleaner has driven in a straight manner.
[0227] Since all areas in which the response motions have been
generated are removed from the second map 801, there is no
restriction on the driving of the robot cleaner. Accordingly, the
robot cleaner may perform a fast cleaning mode (or "quick cleaning
mode) using the second map 801.
[0228] In the quick cleaning mode, the robot cleaner does not visit
the cleaning obstruction areas R1, R2, R3, and R4 that are not
displayed on the second map 801. Thus, it is possible to complete
the cleaning in a short period of time without map lag or wandering
of the robot cleaner.
[0229] In addition, in the fast cleaning mode, it may be controlled
to increase the driving speed of the robot cleaner than before or
to change the driving line to be wider than before.
[0230] For another embodiment, when the cleaning obstruction areas
R1, R2, R3, and R4 are detected from the first map, as illustrated
in FIG. 8B, a second map 802 may be generated by removing all of
the remaining cleaning areas except for the cleaning obstruction
areas R1, R2, R3, and R4. In other words, the second map 802 may be
generated by including only the cleaning obstruction area R1, R2,
R3, and R4 within a boundary B of the first map.
[0231] Since only an area in which the response motion has been
generated is present in the second map 802, the robot cleaner must
pay attention to driving and cleaning. The robot cleaner may
perform a careful cleaning mode using the second map 802.
[0232] In the careful cleaning mode, settings of the driving mode,
cleaning mode, and sensor operation status of the robot cleaner 100
may be determined differently based on the driving status
information recorded in each of the cleaning areas R1, R2, R3, and
R4. Thus, it may be possible to perform an efficient cleaning
operation in a more suitable and subdivided driving mode, cleaning
mode, and operation state of the sensor for each of the cleaning
areas R1, R2, R3, and R4.
[0233] Furthermore, when the careful cleaning mode is performed,
some of the cleaning areas R1, R2, R3, and R4 may be excluded from
the cleaning area based on the driving state information recorded
in each of the cleaning areas R1, R2, R3, and R4.
[0234] Furthermore, in the careful cleaning mode, there is no
limitation on the driving method of the robot cleaner in a place
outside the cleaning areas R1, R2, R3, and R4 within the boundary
B. Therefore, regardless of the driving order in the existing first
map, when cleaning is completed in the first area R1, the third
region R2 close to the first region R1 may be cleaned first.
[0235] In addition, in the careful cleaning mode, the robot cleaner
may be controlled to reduce the driving speed of the robot cleaner
than before, increase the suction power, and change the driving
line to be narrower than before.
[0236] Meanwhile, although not shown, in another embodiment, all of
the plurality of second maps 801 and 801 may be generated, and only
one of them may be used as necessary.
[0237] Furthermore, at normal times (e.g., weekdays), the robot
cleaner cleans the house in a quick cleaning mode using the second
map 801, and at special times (e.g., weekends, before a guest
visit), a plurality of second maps 801 and 801 may be sequentially
used to perform a quick cleaning mode and then a careful cleaning
mode.
[0238] As described above, in the present disclosure, it is
possible to find a cleaning obstruction area by recording driving
state information of a robot cleaner based on a map, and generate a
new map that is highly usable based on the found cleaning area. The
robot cleaner may drive a cleaning area by avoiding the found
cleaning obstruction area using the new map, thereby satisfying
cleaning completion rate and cleaning performance.
[0239] Hereinafter, a method of performing a cleaning operation
using a new map generated based on driving state information will
be described in detail with reference to FIG. 9.
[0240] First, while the robot cleaner 100 performs a cleaning
operation based on the first map, the recorded driving state
information of the main body is stored (S910).
[0241] To this end, the robot cleaner 100 may collect a current
position of the robot cleaner 100 on the first map and driving
state information at that position in real time while driving in a
plurality of cleaning areas corresponding to the first map.
[0242] Here, the driving state information includes a case where
the robot cleaner 100 drives in a straight manner without a
response motion, and a case where a response motion is performed by
sensing a specific situation. The driving state information may be
collected in each cell unit for a plurality of cells constituting
the first map.
[0243] Here, the response motion is generated in response to a
situation sensed through a sensor provided in the robot cleaner 100
or based on information accessed by the robot cleaner.
Specifically, the response motion, which is an operation of the
driving unit 1300 to overcome the sensed situation, may include a
motion of performing, for example, rotation, backward movement,
change-of-direction, stop, change-of-speed, rotation-in-place,
riding, and the like.
[0244] The operation of the driving unit 1300 is executed based on
a control command transmitted from the controller 1800 of the robot
cleaner 100.
[0245] Furthermore, in an example, the robot cleaner 100 may
determine whether a response motion has been generated in
consideration of whether it corresponds to a predetermined driving
path other than a driving direction of the driving unit 1300. For
example, even though the robot cleaner 100 drives in a non-straight
manner in a specific cell of the first map, it may not be
recognized as a response motion when it is to change a driving line
according to a predetermined driving path.
[0246] Furthermore, in an example, the robot cleaner 100 may
determine whether or not a response motion has been generated in
consideration of cleaning operation information of the robot
cleaner 100 in addition to the driving direction of the driving
unit 1300.
[0247] Here, the cleaning operation information may include
information on an amount of dust collected according to an
execution of an original cleaning function of the robot cleaner
100, a rotation speed/suction power of the suction motor, and a
change of the cleaning mode.
[0248] For example, when it is determined that non-straight driving
is performed or stayed for a long time in the corresponding cell as
the suction power is increased or the cleaning mode is changed
since there is a large amount of dust in a specific point/area
while the robot cleaner 100 is cleaning based on the first map, it
may not be recognized as a response motion.
[0249] Furthermore, the driving state information further includes
information on a number of rotations of the wheel, a direction of
rotation of the wheel, and a number of changes in the rotational
direction of the driving unit 1300 when a response motion of the
robot cleaner is generated. This information is collected in a cell
unit of the first map, and may be used as meaningful information in
a cleaning obstruction area described below.
[0250] Next, the robot cleaner 100 may find a plurality of cleaning
areas corresponding to the first map by dividing them into a first
area and a second area based on driving state information stored
therein (S920).
[0251] Here, any one of the first area and the second area denotes
the above-described cleaning obstruction area. Accordingly, when
the first area (the second area) is a cleaning obstruction area,
the second area (first area) refers to the remaining cleaning area
except for the cleaning obstruction area in the first map.
[0252] When cleaning based on the first map is completed, the robot
cleaner 100 extracts an area in which a response motion has been
generated based on driving state information (straight driving or
response motion generation) for each of a plurality of cells
constituting the first map.
[0253] The cleaning obstruction area includes an area in which a
response motion has been generated. In other words, the cleaning
obstruction area corresponds to an area in which a response motion
has been generated or includes an area in which the response motion
has been generated.
[0254] Next, the robot cleaner 100 generates a second map by
removing either one of the first area and the second area from the
first map (S930).
[0255] Specifically, the second map may be generated by removing a
cleaning obstruction area found from the first map. Furthermore,
the second map may consist of a cleaning obstruction area found
from the first map and an outer boundary of the first map.
Furthermore, the second map may be generated by including part of
the cleaning obstruction area and not including part thereof from
the first map.
[0256] Here, the preset condition may be a condition related to the
driving state information of the robot cleaner recorded in the
cleaning obstruction area. For example, the number of rotations of
the wheel, the direction of rotation of the wheel, and the number
of changes in the direction of rotation of the driving unit 1300 in
cells constituting the relevant cleaning obstruction area may be
included as an element for determining whether the cleaning area is
included therein.
[0257] When the second map is generated as described above, the
robot cleaner 100 may perform a cleaning operation in a varied
cleaning mode based on the generated second map (S940).
[0258] Here, the varied cleaning mode may be applied to the
remaining cleaning areas excluding the cleaning obstruction area.
For example, the robot cleaner 100 may clean the remaining cleaning
areas except for the cleaning obstruction area at a high speed
according to the varied cleaning mode using the second map.
[0259] Furthermore, in an example, the varied cleaning mode may be
applied to the cleaning obstruction area. For example, the robot
cleaner 100 may determine an appropriate cleaning mode based on the
driving state information in which the cleaning obstruction area is
stored according to the varied cleaning mode using the second map
or exclude the cleaning obstruction area from the cleaning area. At
this time, when there are a plurality of cleaning obstruction
areas, different cleaning modes may be set according to driving
state information for each of the cleaning obstruction areas.
[0260] In addition, in another example, the varied cleaning mode
may be applied to part of the cleaning obstruction area. For
example, the robot cleaner 100 performs cleaning at a high speed
while the current position of the robot cleaner 100 is located at a
point/area out of the cleaning obstruction area according to the
varied cleaning mode using the second map. Moreover, when it is
sensed that the current position of the robot cleaner 100 has
entered a specific cleaning obstruction area, cleaning may be
performed by changing the driving speed to be slower and the
suction power to be higher based on the driving state
information.
[0261] Moreover, in an embodiment, when the second map is
generated, the generated second map and data related to the second
map may be stored in the memory of the robot cleaner 100 or in a
server (not shown) communicating with the robot cleaner.
[0262] In this case, the controller 1800 of the robot cleaner 100
may call and use the stored second map and the second map-related
data from the memory in response to receiving a driving signal for
a cleaning operation.
[0263] Furthermore, in an example, an application of a terminal
(not shown) in connection with the robot cleaner 100 may be
executed to select whether to perform cleaning based on the first
map or the second map through a displayed user interface (UI). The
robot cleaner 100 may perform a cleaning operation by activating a
cleaning mode corresponding to a map selected through the
terminal.
[0264] Hereinafter, FIGS. 10 to 12 are specific examples of a
process (S940) of performing a cleaning operation in a varied
cleaning mode based on a second map according to the flowchart of
FIG. 9.
[0265] First, FIG. 10 shows an embodiment of performing a cleaning
operation in a varied cleaning mode by avoiding a cleaning
obstruction area based on a second map.
[0266] The controller of the robot cleaner 100 may set a virtual
boundary at a boundary of an area removed from the first map, for
example, the cleaning obstruction area, using the second map 801.
To this end, when the cleaning operation is initiated, the robot
cleaner 100 may first extract information on the cleaning
obstruction areas R1, R2, R3, and R4 from the second map.
[0267] Virtual boundaries W1, W2, W3, and W4 for the cleaning
obstruction areas R1, R2, R3, and R4 may be set based on the
position recognition of the robot cleaner based on the second map
or an external input signal.
[0268] Alternatively, virtual boundaries may be recognized in such
a manner that outer cells among cells in which response motions
have been generated are stored in a buffer while the robot cleaner
is driving based on the first map, and the robot cleaner avoids the
outer cells stored in the buffer based on the current position.
[0269] Alternatively, a virtual wall may be installed at a boundary
of the cleaning obstruction area, and a magnetic sensor or the like
may be activated while the robot cleaner 100 is cleaning based on
the second map, thereby being controlled to drive by avoiding the
virtual wall.
[0270] In addition, when part of the boundary corresponds to a
boundary 1010 of the second map 801, as in the first cleaning
obstruction area R1 and the fourth cleaning obstruction area R4 in
FIG. 10, boundary setting for the part thereof may be omitted.
[0271] In a case where the virtual boundaries are set in this way,
when the robot cleaner approaches the boundaries of the cleaning
obstruction areas R1, R2, R3, and R4 while performing cleaning
based on the second map, the robot cleaner performs an avoidance
operation not to enter the cleaning obstruction areas R1, R2, R3,
and R4.
[0272] Since such an avoidance operation is much faster and simpler
than allowing the robot cleaner to enter the cleaning obstruction
area R1, R2, R3, and R4 so as to perform a response motion, the
robot cleaner 100 may quickly clean the cleaning areas except for
the cleaning obstruction areas R1, R2, R3, and R4 using the second
map 801.
[0273] In other words, the robot cleaner may perform cleaning in a
"quick cleaning mode" on a cleaning area excluding the cleaning
obstruction areas R1, R2, R3, and R4.
[0274] In the quick cleaning mode, the driving speed of the robot
cleaner 100 may be increased, the width of the driving line may be
further increased, unnecessary sensors (e.g., cliff sensor) may be
switched to an inactive state to reduce battery consumption, or the
sensitivity level of the sensor may be decreased than before.
[0275] Next, FIG. 11 is an embodiment in which a cleaning operation
is performed on part of a cleaning obstruction area in a varied
cleaning mode based on a second map.
[0276] The controller of the robot cleaner 100 may perform a
cleaning operation in a varied cleaning mode using the second map
802 consisting of only the boundary B of the first map and the
detected cleaning obstruction areas R1, R2, R3, R4.
[0277] At this time, there is no need to additionally set virtual
boundaries for the cleaning obstruction areas R1, R2, R3, and R4.
This is because an inside of the cleaning obstruction areas R1, R2,
R3, and R4 is a cleaning area, and an outside of the cleaning
obstruction areas R1, R2, R3, and R4 is an area that allows free
driving though it is excluded from the cleaning area.
[0278] However, some of the cleaning obstruction areas that cause
map lag or constrain the robot cleaner may be preferably removed
from the second map or classified as a non-cleaning area. In this
case, virtual boundaries must be set for some of the cleaning
obstruction areas.
[0279] To this end, when cleaning is performed based on the second
map, the controller of the robot cleaner 100 recognizes its current
location, and then determines whether to classify the area as a
cleaning area, remove it from the second map, or classify it as a
non-cleaning area based on the driving state information recorded
in the cleaning area.
[0280] For example, when the rotation of the driving unit 1300 of
the robot cleaner 100 exceeds 5 times in a target cleaning
obstruction area, it may be removed from the second map or
classified as a non-cleaning area. On the contrary, when the
rotation of the driving unit 1300 of the robot cleaner 100 is less
than 5 times in the target cleaning obstruction area, it is
recognized as a cleaning area of the second map to perform a
cleaning operation in a "careful cleaning mode".
[0281] Furthermore, for example, while the driving unit 1300 of the
robot cleaner 100 continuously rotates in the target cleaning
obstruction area, a case where the time taken to exit the area
exceeds a reference time (e.g., above 1 minute) may be removed from
the second map or classified as an non-cleaning area.
[0282] In this way, in the areas R1, R2, R3, and R4 of the second
map 802, a cleaning operation is performed in a "careful cleaning
mode" for the areas 1110 and 1120 classified as cleaning areas. In
addition, virtual boundaries W3 and W4 using virtual walls are set
not to allow the robot cleaner 100 to enter the cleaning
obstruction areas R2 and R4 classified as non-cleaning areas in the
second map 802.
[0283] FIG. 11 is an example showing a varied second map 802' in
which the cleaning area and the non-cleaning area are displayed in
a classified manner.
[0284] In the "careful cleaning mode", a driving speed of the robot
cleaner 100 may be reduced, a sensitivity level of a sensor such as
an obstacle sensor may be increased, and a rotation speed/suction
power of the suction motor may be increased.
[0285] For example, while the robot cleaner 100 cleans the areas
1110 and 1120, the driving speed may be reduced to 1/2 compared to
the previous one, the height of obstacle determination may be
reduced to 1/2 compared to the previous one, and the suction power
may be doubled to perform a cleaning operation. This setting may be
automatically returned to the previous value when the robot cleaner
100 exits the areas 1110 and 1120.
[0286] Furthermore, subsequent to cleaning completion for one area
1110, the robot cleaner may be operated to temporarily release the
careful cleaning mode while moving to another area 1120, and reset
the careful cleaning mode when entering the other area 1120.
[0287] On the other hand, although not shown, in an embodiment, the
robot cleaner 100 may first perform cleaning in a quick cleaning
mode using the second map 801 by combining the examples described
in FIGS. 10 and 11, and perform cleaning in a careful cleaning mode
using the second map 802 subsequent to the completion of the first
cleaning.
[0288] At this time, when the battery is sensed to be less than a
reference value after completing the cleaning in the quick cleaning
mode, the controller of the robot cleaner 100 may return to the
charging station instead of performing the careful cleaning mode.
In this case, the reference value does not denote a general
low-battery state, but denotes that the remaining charge amount of
the battery is insufficient to complete the careful cleaning
mode.
[0289] Hereinafter, FIGS. 12 and 13 are modified embodiments of the
process (S940) of performing a cleaning operation in a varied
cleaning mode based on a second map according to the flow chart of
FIG. 9. Accordingly, it should be noted that even if the
configuration is not specifically described in FIGS. 12 and 13, the
configurations described with reference to FIG. 9 may be similarly
applied to FIGS. 12 and 13.
[0290] FIG. 12 shows a view in which a varied second mane 803 is
generated by layering a second map 801 consisting of part of
cleaning obstruction areas ("cleaning attention areas") and areas
excluding the cleaning obstruction areas ("quick cleaning areas")
based on a second map 802' consisting of only the cleaning
obstruction areas or partially consisting of the cleaning
obstruction areas.
[0291] The varied second map 803 may include a cleaning attention
area, a quick cleaning area, and non-cleaning areas ER4 and
ER4.
[0292] The robot cleaner 100 may perform a cleaning operation in
the careful cleaning area and the quick cleaning area in different
variable cleaning modes based on the varied second map.
Furthermore, a virtual boundary using a virtual wall or the like
may be set so as not to enter the non-cleaning areas ER4 and ER4
when the driving path 1201 of the robot cleaner 100 is set.
[0293] Hereinafter, FIG. 13 is a flowchart for explaining a method
of performing a cleaning operation in different cleaning modes by
adding a cleaning attention area to a second map generated based on
driving state information of the robot cleaner.
[0294] First, the robot cleaner 100 performs driving/cleaning based
on the first map, and generates a second map in which cleaning
obstruction areas are removed from the first map (S1310).
[0295] Next, the controller of the robot cleaner 100 sets cleaning
areas corresponding to the generated second map, straight driving
areas, as a first cleaning mode (S1320).
[0296] Here, the first cleaning mode may be a driving manner
different from a zigzag manner. Furthermore, the first cleaning
mode may be a cleaning mode in which the driving speed is faster
compared to the existing one, some sensors are deactivated or a
sensitivity level thereof is reduced.
[0297] Next, the controller of the robot cleaner 100 sets part of
the cleaning area as a cleaning attention area and adds it to the
second map (S1330). At this time, an area of the first map that is
not included in the second map may be classified as a non-cleaning
area, and completely removed from the cleaning area.
[0298] The cleaning attention areas added to the second map may be
classified into different cleaning attention areas based on the
driving state information of the robot cleaner in the relevant
areas.
[0299] When the second map is varied in this way, the controller of
the robot cleaner sets the cleaning attention area added to the
second map to a second cleaning mode different from the set first
cleaning mode (S1340).
[0300] Specifically, for example, based on the driving state
information, a cleaning obstruction area in which the rotation of
the robot cleaner exceeds 5 times is classified as a non-cleaning
area. In addition, a cleaning obstruction area in which a motion
corresponding to vision bumping occurs due to wheel slip of the
robot cleaner based on the driving state information is classified
as a non-cleaning area because it causes map lag.
[0301] In a first cleaning caution area where the robot cleaner
rotates less than 5 times and a response motion such as obstacle
avoidance has been generated, it is set to a careful cleaning mode
having a half of the driving speed of the robot cleaner, a half of
the height of the obstacle determination, and about two times of
the suction power of the suction motor.
[0302] Furthermore, in a second cleaning area where the robot
cleaner has a lot of shaking and the floor is uneven, it is set to
a careful cleaning mode having a half of the driving speed of the
robot cleaner, and a minimum value, for example, one-fifth of the
height of obstacle determination.
[0303] In addition, a third cleaning attention area in which a
cliff response motion of the robot cleaner, a wheel falling off is
generated may have a dangerous shape, and is set to a careful
cleaning mode having a minimum value, for example, one-fifth of the
driving speed of the robot cleaner, and a half of the height of
obstacle determination.
[0304] As described above, in the present disclosure, the quick
cleaning area is set to a quick cleaning mode, and the cleaning
attention area is is set to a cleaning mode in which at least one
of a driving speed of the robot cleaner, a sensitivity level or
reference value of the sensor, and a rotation speed/suction power
of the suction motor provided in the main body is changed based on
driving state information recorded in each cleaning obstruction
area.
[0305] Meanwhile, in an example, the setting of the second cleaning
mode may be performed when the robot cleaner 100 is close to the
relevant cleaning attention area. To this end, the robot cleaner
100 must determine its current position in real time based on the
second map.
[0306] Next, the controller of the robot cleaner controls the robot
cleaner body to perform a cleaning operation in different cleaning
modes for the plurality of cleaning areas based on the changed
second map (S1350).
[0307] Specifically, the controller of the robot cleaner may
increase the sensitivity level of at least one sensor (or reduce
the reference value of a sensor) provided in the robot cleaner body
than before while performing a cleaning operation on a cleaning
attention region using the changed second map.
[0308] Furthermore, the controller of the robot cleaner may recover
or decrease the changed sensitivity level of the sensor (or recover
or increase the reference value of the sensor) in response to
sensing that the current position of the robot cleaner is out of
the cleaning area.
[0309] The controller of the robot cleaner may output a control
command for increasing a rotation speed of the suction motor
provided in the robot cleaner body than before while performing a
cleaning operation for the cleaning attention area using the
changed second map.
[0310] Furthermore, the controller of the robot cleaner may further
reduce the driving speed of the main body by the driving unit than
before while performing a cleaning operation for the cleaning
attention area using the changed second map.
[0311] As a last example, FIGS. 14A and 14B show an example of
updating a map in which a cleaning obstruction area is added or
removed based on a change in driving state information collected
based on a first map or a second map.
[0312] The robot cleaner according to the present disclosure may
continuously collect driving state information of the main body as
described in detail above while performing cleaning based on the
second map. Accordingly, it may be possible to additionally find a
cleaning obstruction area or change the existing cleaning
obstruction area to a quick cleaning area or a non-cleaning
area.
[0313] For example, referring to FIG. 14A, when a complicated
response motion is generated on the driving path 1401 while
cleaning is performed based on the second map 801 from which the
cleaning obstruction area has been removed, the relevant area R5 is
now not suitable for performing the cleaning operation in the quick
cleaning mode. Accordingly, the updated second map 801A may be
generated by removing the relevant are R5 from the second map
801.
[0314] Furthermore, for example, referring to FIG. 14B, subsequent
to the generation of the second map, when driving state information
is recorded as there is no response motion in the area R1 removed
from the second map 801 based on the existing first map, a cleaning
operation may now be performed for the area R1 in a quick cleaning
mode. Accordingly, the updated second map 801B may be generated by
adding the relevant region R1 to the second map 801.
[0315] As described above, a robot cleaner and an operation method
thereof according to an embodiment of the present disclosure may
generate a map that is robust to various environmental variables
and is highly usable without relying on a sensor. In addition,
since it may be possible to find a cleaning obstruction area from
an existing map with only the driving status information of the
robot cleaner without having a sensor, and a new cleaning mode may
be developed and set based thereon, thereby allowing both cleaning
efficiency and cleaning time to be satisfied. For example, it may
be possible to quickly clean the remaining areas except for the
cleaning obstruction area that it takes a long time to clean and
causes the map to slip. Moreover, it may be possible to reduce the
driving speed during the cleaning of the found cleaning obstruction
area, increase the sensitivity level of the sensor, and increase
the suction power, thereby improving the performing of cleaning. In
other words, it may be possible to shorten the cleaning time and
improve the cleaning efficiency at the same time.
[0316] The present disclosure described above may be implemented as
computer-readable codes on a program-recorded medium. The computer
readable medium includes all kinds of recording devices in which
data readable by a computer system is stored. Examples of the
computer-readable medium include a hard disk drive (HDD), a solid
state disk (SSD), a silicon disk drive (SDD), a ROM, a RAM, a
CD-ROM, a magnetic tape, a floppy disk, an optical data storage
device and the like, and may also be implemented in the form of a
carrier wave (e.g., transmission over the Internet). In addition,
the computer may also include the controller 1800. The above
detailed description should not be limitedly construed in all
aspects and should be considered as illustrative. The scope of the
present invention should be determined by rational interpretation
of the appended claims, and all changes within the scope of
equivalents of the present invention are included in the scope of
the present disclosure.
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